Head-to-head
Claude Haiku 4.5 vs GPT-5.5: which AI model wins in 2026?
Claude Haiku 4.5 ($5/1M out) and GPT-5.5 ($30/1M out) are two of the most-used AI models in 2026. Across 5 community votes, Claude Haiku 4.5 leads with 67% approval.
Quick verdict
On Reasoning, pick GPT-5.5: the arena rates it 5/5 against 3/5 for Claude Haiku 4.5. On budget, Claude Haiku 4.5 wins: it starts at $5/1M out versus $30/1M out for GPT-5.5.
Line-by-line comparison
Strengths and weaknesses
Claude Haiku 4.5
- 73.3% on SWE-bench Verified, about 90% of Sonnet 4.5's agentic coding at one third of the price
- Fast: more than 2x Sonnet 4 speed per Anthropic, with launch customers reporting 4-5x faster than Sonnet 4.5; ~92-110 output tok/s measured by Artificial Analysis
- Devs report precise, localized code edits that avoid touching irrelevant code, better than GPT-5 mini class in early testing
- Supports both vision input and extended thinking, rare at this price tier at launch
- Well suited as worker model in multi-agent setups (Sonnet/Opus plans, parallel Haiku sub-agents execute)
- Prompt caching reads at $0.10/1M and 50% Batch API discount cut effective cost further
- $5/1M output is pricey for a small model: Gemini Flash and GPT mini tiers undercut it several-fold on output-heavy tasks
- 200K context (vs 1M for Sonnet 5/Opus siblings) and 64K max output limit large-codebase and long-output work
- Mediocre cross-domain reasoning: users report weak results on GPQA, MedQA, MMMU style knowledge tasks
- Throughput varies widely in practice (82-208 tok/s reported) and quality degrades on long 7-8+ minute agentic sessions
- Knowledge cutoff (reliable to Feb 2025) is dated by mid-2026 standards
GPT-5.5
- 1M-token context window (1,050,000) with 128K max output and reasoning effort tunable from none to xhigh
- State-of-the-art ARC-AGI-2 at 85.0% (vs 73.3% for GPT-5.4) and Terminal-Bench 2.0 at 82.7%
- Strong agentic coding autonomy: devs report it one-shots tasks that took GPT-5.4 multiple turns and fixes its own mistakes; +50 points on Code Arena vs GPT-5.4
- Aggressive discounts: 90% off cached input ($0.50/1M) and 50% off via Batch or Flex ($2.50/$15)
- Fast for a frontier reasoner: devs say it is the first GPT model comfortable to run at medium or low thinking effort
- List price doubled vs GPT-5.4 ($5/$30 vs $2.50/$15) for the same 1M-token context window
- Overly literal instruction-following: devs report it fails to infer intent in obvious places where Claude succeeds
- Trails Claude Opus 4.8 on SWE-bench Pro (58.6% vs 69.2%); HN developers still favor Claude roughly 2:1 for coding
- Sometimes too conservative with code changes or skips deep reasoning entirely, answering immediately on complex prompts
- Long-context surcharge: prompts over 272K input tokens are billed 2x input and 1.5x output for the whole session
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on Claude Haiku 4.5
Pick Haiku 4.5 if you are on the Anthropic stack and need near-Sonnet coding quality at low latency and a third of the price: it is a massive step up from Haiku 3.5 and excels as the worker model in multi-agent pipelines. It remains Anthropic's current small model as of July 2026, so it is the default cheap tier for Claude-based products. Avoid it for deep cross-domain reasoning, very large codebases (200K context cap), or pure cost-per-token shopping, where Gemini Flash and GPT mini tiers are now cheaper, and step up to Sonnet 5 when quality matters more than speed.
The arena’s verdict on GPT-5.5
Pick GPT-5.5 over GPT-5.4 if you need stronger agentic autonomy, terminal-heavy workflows, or SOTA abstract reasoning, but know the list price doubled from GPT-5.4's $2.50/$15 to $5/$30 while the 1M-token context stayed the same. Teams doing high-stakes multi-file refactoring may still prefer Claude Opus, which leads SWE-bench Pro (69.2% vs 58.6%) and infers intent better from loose prompts. Budget-sensitive users should mind the 272K-token surcharge and reports of faster limit burn, and lean on caching, Batch, or Flex to halve costs.
What the crowd says
On Claude Haiku 4.5
“The precise localized edits are the underrated feature. It fixes the line that needs fixing and leaves the rest alone. GPT mini class models keep rewriting half my file.”
“Haiku 4.5 gives me about 90% of Sonnet agentic coding at a third of the price, and it is fast enough that edit loops feel instant. My default for quick fixes now.”
On GPT-5.5
“It is painfully literal. Where Claude infers intent in obvious places, 5.5 wants everything spelled out. And the price doubled vs 5.4 for the same 1M context.”
“85 on ARC-AGI-2 and you can feel it. Stuff that used to stall my agent just resolves now. 1M context with 128K output covers every workflow I have.”
“5.5 one-shots tasks that took 5.4 three turns, and it fixes its own mistakes mid-run instead of doubling down. The reasoning effort dial from none to xhigh is genuinely useful.”
Keep comparing
Frequently asked questions
Is Claude Haiku 4.5 better than GPT-5.5?
The crowd currently sides with Claude Haiku 4.5: 67% recommend it, versus 57% for GPT-5.5 (5 votes). On Reasoning, GPT-5.5 rates higher (5/5 vs 3/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, Claude Haiku 4.5 or GPT-5.5?
Claude Haiku 4.5 is cheaper: it starts at $5/1M out, while GPT-5.5 starts at $30/1M out.
How much do Claude Haiku 4.5 and GPT-5.5 cost per 1M tokens?
Claude Haiku 4.5: $1/1M in per 1M input tokens, $5/1M out per 1M output tokens. GPT-5.5: $5/1M in per 1M input tokens, $30/1M out per 1M output tokens.